Hypertrophic Cardiomyopathy History

It was December 9^th, 1989, when one of Loyola Marymount’s strongest inside players, Hank Gathers, collapsed during the middle of a collegiate level basketball game against UC Santa Barbara. Measuring in at 6’7” and weighing 210 pounds, Gathers was diagnosed with exercise-induced ventricular tachycardia, or in layman’s terms, an abnormal heartbeat. Even with the concerning nature of this condition, Gathers continued to compete, and at one point was even guarded by future NBA first-round draft pick Shaquille O’Neal. It wasn’t until Sunday, March 4^th, 1990, where Gathers again collapsed during a game, however, this time it was fatal. At 23 years old, Hank Gathers had passed away from a heart-muscle disorder known as hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the leading cause of athletic fields deaths in young individuals and affects about one in 500 people (1,2). This condition results in increased stiffness in the left ventricle of the heart, which can lead to a multitude of symptoms such as weakness, fainting, and sudden cardiac death. HCM is commonly an autosomal dominant inherited disorder attributed to mutations in sarcomere genes, which can be diagnosed using genetic testing. Here in this blog, we will detail how VarSeq can be customized to identify variants associated with cardiomyopathy and how to implement VSClinical to evaluate a causal HCM variant further using the ACMG guidelines.

Case Report

A 32-year old Caucasian male presented with chronic progressive chest pain. He was initially started on treatment for acute coronary syndrome. Diagnosis of HCM was missed on echocardiography but made on subsequent catheterization and cardiac MRI. He improved with metroprolol, had a work-up for implantable cardioverter-defibrillator placement, and was referred to genetic testing (3).

Genetic Testing

Starting with a targeted gene panel for cardiomyopathy, we began by filtering on quality fields present in the Variant Calling Format (VCF) file. Using read depth, genotype qualities, and zygosity, VarSeq identified approximately 32,000 high-quality variants (Figure 1A). Next, we filtered for variants that had an alternate allele frequency (AF) less than 1% in gnomAD Exomes Variant Frequencies as well as variants within genes most highly associated with HCM using the integrated PhoRank algorithm (Figure 1B). Following this filter logic, we then used the ACMG Classifier to isolate a single missense variant in the Myosin Heavy Chain 7 (MYH7) gene (NM_000257.3:c.2334C>G) that was auto-classified as Pathogenic (Figure 1C). This variant was then pulled into VSClinical to be evaluated according to the ACMG guidelines.

In the Population tab of VSClinical, both gnomAD Exomes and 1000 Genomes identified that the variant was novel among all individual subpopulations. This evidence applied PM2 to the evaluation as the variant is absent from controls in population catalogs. In the Gene Impact tab, multiple records were present in ClinVar of neighboring missense variants classified as Likely Pathogenic and Pathogenic in the same exon (Figure 2). This applied PM1 to the classification, as the variant was found to be located in a mutational hotspot. In total, the MYH7 gene was also found to have 227 pathogenic missense variants with a low rate of benign variants, which applied PP2 to the variant classification. Lastly, we were able to assess relevant literature in the Studies tab and identified two previous ClinVar Assessments for the same variant. Both assessments reached a final classification of Pathogenic and were associated with the same HCM disorder (Figure 3). Since both studies reported on the same amino acid change, both PS1 and PM5 were applied to the evaluation resulting in a final classification according to the ACMG guidelines of Pathogenic (Figure 4). This was then rendered in a clinical report (Figure 5).

In summary, Hypertrophic Cardiomyopathy (HCM) is the leading cause of sudden cardiac death in young individuals, such as Hank Gathers and other athletes, but also impacts 1 in 500 persons (2). Mutations associated with HCM primarily reside in sarcomere genes, with most mutations being associated with the gene encoding beta-myosin heavy chain (MYH7) (2). From a cardiomyopathy targeted panel, we implemented a filter chain to identify high-quality and rare variants that were highly associated with HCM and auto-classified as Likely Pathogenic or Pathogenic using the ACMG Classifier. In VSClinical, we evaluated this variant according to the ACMG criteria and identified literature that brought the final variant classification to Pathogenic, which could then be saved in your internal catalog and rendered in a clinical report.

Hopefully, this was an informative blog post on how you can use VarSeq and VSClinical to isolate clinically relevant variants from your NGS data. If you have any questions or comments about the information displayed here or about our software, please don’t hesitate to reach out and contact us.  

Check out some of the other blogs in this series:

• Variant Interpretation with VSClinical: Clinical Example for Congenital Indifference to Pain
• Variant Interpretation with VSClinical: Evaluation of an X-linked recessive mutation
• Variant Interpretation with VSClinical: Congenital Myasthenic Syndromes (CMS)
• Variant Interpretation with VSClinical: Huntington’s Disease (HD)
• Variant Interpretation with VSClinical: Non-Small Cell Lung Cancer
• Variant Interpretation with VSClinical: RET-KIF5b Gene Fusion

1. B J Maron. Distinguishing hypertrophic cardiomyopathy from athlete’s heart: a clinical problem of increasing magnitude and significance. Heart. 2005 Nov; 91(11): 1380-1382. 
2. Sara L. Van Driest et al. Comprehensive Analysis of the Beta-Myosin Heavy Chain Gene in 389 Unrelated Patients with Hypertrophic Cardiomyopathy”. Journal of the American College of Cardiology. Volume 44, Issue 3, 4 Aug. 2004: 602-610.
3. Tanya Doctorian, Willian J. Mosley, Bao Bo. Apical Hypertrophic Cardiomyopathy: Case Report and Literature Review. The American Journals of Case Reports. 2017; 18: 525-528.